ESS on-line Manuals Expert Systems: Rules

Shared Tools: Reference Manual

Release Level	5.4
Release Date	2008 10
Revision Level	1.0

Last modified on: Monday, 29-Sep-08 13:32 CEST

XPS: Backward Chaining Rules

Backward Chaining Rules define how values for DESCRIPTORs are derived from values of other DESCRIPTORs, user inputs, simulation model results or other information available (data bases, GIS, etc.).

Rule Syntax

RULE <rule#>
IF   <condition>
THEN <action>
ENDRULE
<condition> := <condition <logical operator> <condition>
            := descriptor <comparative operator> <operand>
            := descriptor <singular operator>
            := TRUE

<action>    := descriptor = <operand>
            := descriptor <meta operator> <constant>
<operand>   := <operand> <arithmetic operator> <operand>
            := descriptor
            := <constant>
<logical operator>     := AND | OR
<comparative operator> :=  < | > | <= | >= | == | !=
<singular operator>    := EXISTS | NOT_EXISTS
<arithmetic operator>  := [ | ] | * | / | + | - 
<meta operator>        := INCREASES_BY | DECREASES_BY
                       := BECOMES
<constant>  := string
            := number

Rules can result in the absolute assignment of DESCRIPTOR values, their relative, incremental modification, or they can be used to control the inference strategy depending on context. Rules can also include simple formulas; more complex functions can be used through the generic model interface.

An example for a rule used in the reservoir expert system is:

   RULE 1020231
   IF      average_reservoir_depth  == small
   AND     retention_time            < 30
   THEN    reservoir_stratification  = unlikely
   ENDRULE

Also, the user can call up a knowledge base browser, that allows to navigate in the tree structure of the knowledge base within the context of individual problems. The browser can descend the inference tree, displaying sets of rules referring to a list of DESCRIPTORs and allow to inspect individual DESCRIPTOR definitions.

The possibility to integrate models in place of rules in an expert system and at the same time use embedded rule-based components in models provides a very rich repertoire of building blocks for interactive software systems.

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